@article {JUMET2023100059, title = {Fluidically programmed wearable haptic textiles}, journal = {Device}, year = {2023}, pages = {100059}, abstract = {

Summary Haptic feedback offers a useful mode of communication in visually or auditorily noisy environments. The adoption of haptic devices in our everyday lives, however, remains limited, motivating research on haptic wearables constructed from materials that enable comfortable and lightweight form factors. Textiles, a material class fitting these needs and already ubiquitous in clothing, have begun to be used in haptics, but reliance on arrays of electromechanical controllers detracts from the benefits that textiles offer. Here, we mitigate the requirement for bulky hardware by developing a class of wearable haptic textiles capable of delivering high-resolution information on the basis of embedded fluidic programming. The designs of these haptic textiles enable tailorable amplitudinal, spatial, and temporal control. Combining these capabilities, we demonstrate wearables that deliver spatiotemporal cues in four directions with an average user accuracy of 87\%. Subsequent demonstrations of washability, repairability, and utility for navigational tasks exemplify the capabilities of our approach.

}, keywords = {analog control, fluidic control, haptic sleeve, human-machine interaction, human-robot interaction, Navigation, point force, smart textiles, spatiotemporal haptics, tactile cues}, issn = {2666-9986}, doi = {https://doi.org/10.1016/j.device.2023.100059}, url = {https://www.sciencedirect.com/science/article/pii/S2666998623000832}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/DeviceJumet2023.pdf}, author = {Barclay Jumet and Zane A. Zook and Anas Yousaf and Anoop Rajappan and Doris Xu and Te Faye Yap and Nathaniel Fino and Zhen Liu and Marcia K. O{\textquoteright}Malley and Daniel J. Preston} } @article {pezent2023AIS, title = {Multisensory Pseudo-Haptics for Rendering Manual Interactions with Virtual Objects}, journal = {Advanced Intelligent Systems}, volume = {n/a}, number = {n/a}, year = {2023}, pages = {2200303}, abstract = {

Recent advances in extended reality (XR) technologies make seeing and hearing virtual objects commonplace, yet strategies for synthesizing haptic interactions with virtual objects continue to be limited. Two design principles govern the rendering of believable and intuitive haptic feedback: movement through open space must feel {\textquotedblleft}free{\textquotedblright} while contact with virtual objects must feel stiff. Herein, a novel multisensory approach that conveys proprioception and effort through illusory visual feedback and refers to the wrist, via a bracelet interface, discrete and continuous interaction forces that would otherwise occur at the hands and fingertips, is presented. Results demonstrate that users reliably discriminate the stiffness of virtual buttons when provided with multisensory pseudohaptic feedback, comprising tactile pseudohaptic feedback (discrete vibrotactile feedback and continuous squeeze cues in a bracelet interface) and visual pseudohaptic illusions of touch interactions. Compared to the use of tactile or visual pseudohaptic feedback alone, multisensory pseudohaptic feedback expands the range of physical stiffnesses that are intuitively associated with the rendered virtual interactions and reduces individual differences in physical-to-virtual stiffness mappings. This multisensory approach, which leaves users{\textquoteright} hands unencumbered, provides a flexible framework for synthesizing a wide array of touch-enabled interactions in XR, with great potential for enhancing user experiences.

}, keywords = {augmented reality, bracelet, haptic interaction, haptics, Virtual reality, wearables}, doi = {https://doi.org/10.1002/aisy.202200303}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/aisy.202200303}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Advanced\%20Intelligent\%20Systems\%20-\%202023\%20-\%20Pezent\%20-\%20Multisensory\%20Pseudo\%E2\%80\%90Haptics\%20for\%20Rendering\%20Manual\%20Interactions\%20with\%20Virtual.pdf}, author = {Pezent, Evan and Macklin, Alix and Yau, Jeffrey M. and Colonnese, Nicholas and O{\textquoteright}Malley, Marcia K.} } @article {macklin2023toh, title = {Representational Similarity Analysis for Tracking Neural Correlates of Haptic Learning on a Multimodal Device}, journal = {IEEE Transactions on Haptics}, volume = {16}, number = {3}, year = {2023}, month = {July-September}, pages = {424-435}, doi = {10.1109/TOH.2023.3303838}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Macklin\%20et\%20al.\%202023.pdf}, author = {Macklin, Alix S and Yau, Jeffrey M and Fischer-Baum, Simon and O{\textquoteright}Malley, Marcia K} } @article {dupont2021decade, title = {A decade retrospective of medical robotics research from 2010 to 2020}, journal = {Science Robotics}, volume = {6}, number = {60}, year = {2021}, pages = {eabi8017}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/scirobotics2021abi8017.pdf}, author = {Dupont, Pierre E and Nelson, Bradley J and Goldfarb, Michael and Hannaford, Blake and Menciassi, Arianna and O{\textquoteright}Malley, Marcia K and Simaan, Nabil and Valdastri, Pietro and Yang, Guang-Zhong} } @article {yousaf2021design, title = {Design and Characterization of a Passive Instrumented Hand}, journal = {ASME Letters in Dynamic Systems and Control}, volume = {1}, number = {1}, year = {2021}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/ALDSC-19-1082-1_Two_Col.pdf}, author = {Yousaf, Saad N and Joshi, Victoria S and Britt, John E and Rose, Chad G and O{\textquoteright}Malley, Marcia K} } @article {2002, title = {Evaluating the Effect of Stimulus Duration on Vibrotactile Cue Localizability with a Tactile Sleeve}, journal = {IEEE Transactions on Haptics}, volume = {14}, number = {2}, year = {2021}, month = {April-June 2021}, pages = {328-334}, doi = {10.1109/TOH.2021.3079727}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Macklin_ToH2021.pdf}, author = {Macklin, Alix S. and Yau, Jeff and O{\textquoteright}Malley, Marcia K} } @article {1961, title = {Multi-Sensory Stimuli Improve Distinguishability of Cutaneous Haptic Cues}, journal = {IEEE Transactions on Haptics}, volume = {13}, number = {2}, year = {2020}, month = {April-June 2020}, pages = {286-297}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Sullivan_ToH_2020_multi-sensory.pdf}, author = {Sullivan, Jennifer L and Dunkelberger, Nathan and Bradley, Joshua and Young, Joseph and Israr, Ali and Lau, Frances and Klumb, Keith and Abnousi, Freddy and O{\textquoteright}Malley, Marcia K} } @article {BHAGAT2020102502, title = {Neural activity modulations and motor recovery following brain-exoskeleton interface mediated stroke rehabilitation}, journal = {NeuroImage: Clinical}, volume = {28}, year = {2020}, pages = {102502}, abstract = {

Brain-machine interfaces (BMI) based on scalp EEG have the potential to promote cortical plasticity following stroke, which has been shown to improve motor recovery outcomes. However, the efficacy of BMI enabled robotic training for upper-limb recovery is seldom quantified using clinical, EEG-based, and kinematics-based metrics. Further, a movement related neural correlate that can predict the extent of motor recovery still remains elusive, which impedes the clinical translation of BMI-based stroke rehabilitation. To address above knowledge gaps, 10 chronic stroke individuals with stable baseline clinical scores were recruited to participate in 12 therapy sessions involving a BMI enabled powered exoskeleton for elbow training. On average, 132\ {\textpm}\ 22 repetitions were performed per participant, per session. BMI accuracy across all sessions and subjects was 79\ {\textpm}\ 18\% with a false positives rate of 23\ {\textpm}\ 20\%. Post-training clinical assessments found that FMA for upper extremity and ARAT scores significantly improved over baseline by 3.92\ {\textpm}\ 3.73 and 5.35\ {\textpm}\ 4.62 points, respectively. Also, 80\% participants (7 with moderate-mild impairment, 1 with severe impairment) achieved minimal clinically important difference (MCID: FMA-UE \>5.2 or ARAT \>5.7) during the course of the study. Kinematic measures indicate that, on average, participants{\textquoteright} movements became faster and smoother. Moreover, modulations in movement related cortical potentials, an EEG-based neural correlate measured contralateral to the impaired arm, were significantly correlated with ARAT scores (ρ\ =\ 0.72, p\ \<\ 0.05) and marginally correlated with FMA-UE (ρ\ =\ 0.63, p\ =\ 0.051). This suggests higher activation of ipsi-lesional hemisphere post-intervention or inhibition of competing contra-lesional hemisphere, which may be evidence of neuroplasticity and cortical reorganization following BMI mediated rehabilitation therapy.

}, keywords = {Brain-machine interface, Clinical trial, Exoskeletons, Movement related cortical potentials, stroke rehabilitation}, issn = {2213-1582}, doi = {https://doi.org/10.1016/j.nicl.2020.102502}, url = {http://www.sciencedirect.com/science/article/pii/S2213158220303399}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/NeuroImage_2020_Bhagat_BMI_EEG_exo.pdf}, author = {Nikunj A. Bhagat and Nuray Yozbatiran and Jennifer L. Sullivan and Ruta Paranjape and Colin Losey and Zachary Hernandez and Zafer Keser and Robert Grossman and Gerard E. Francisco and Marcia K. O{\textquoteright}Malley and Jose L. Contreras-Vidal} } @proceedings {1962, title = {Design and Characterization of a Passive Instrumented Hand}, year = {2019}, month = {10/2019}, doi = {https://doi.org/10.1115/DSCC2019-9082}, url = {https://asmedigitalcollection.asme.org/DSCC/proceedings/DSCC2019/59148/V001T05A007/1070466?searchresult=1}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Instrumented_Hand_DSCC_Revised-compressed.pdf}, author = {Yousaf, Saad N and Joshi, Victoria S and Britt, John E and Rose, Chad G and O{\textquoteright}Malley, Marcia K} } @proceedings {1816, title = {Improving robotic stroke rehabilitation by incorporating neural intent detection: Preliminary results from a clinical trial}, year = {2017}, month = {07/2018}, publisher = {IEEE}, address = {London, UK}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Sullivan_ICORR\%202017_BMI\%20Exo.pdf}, author = {Sullivan, J.L. and Bhagat, N.A. and Yozbatiran, N. and Paranjape, R. and Losey, C.G. and Grossman, R.G. and Contreras-Vidal, J.L. and Francisco, G.E. and O{\textquoteright}Malley, M.K.} } @article {PMID:28857769, title = {Robot-Assisted Training of Arm and Hand Movement Shows Functional Improvements for Incomplete Cervical Spinal Cord Injury}, journal = {American Journal of Physical Medicine \& Rehabilitation}, volume = {96}, number = {10}, year = {2017}, month = {10/2017}, pages = {S171{\textemdash}S177}, issn = {0894-9115}, doi = {10.1097/phm.0000000000000815}, url = {https://doi.org/10.1097/PHM.0000000000000815}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/francisco2017AJPRM.pdf}, author = {Francisco, Gerard E and Yozbatiran, Nuray and Berliner, Jeffrey and O'Malley, Marcia K and Pehlivan, Ali Utku and Kadivar, Zahra and Fitle, Kyle and Boake, Corwin} } @article {PMID:28944083, title = {White matter changes in corticospinal tract associated with improvement in arm and hand functions in incomplete cervical spinal cord injury: pilot case series}, journal = {Spinal Cord Series and Cases}, volume = {3}, year = {2017}, pages = {17028}, issn = {2058-6124}, doi = {10.1038/scsandc.2017.28}, url = {https://doi.org/10.1038/scsandc.2017.28}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Yozbatiran2017SpinalCordSeries.pdf}, author = {Yozbatiran, Nuray and Keser, Zafer and Hasan, Khader and Stampas, Argyrios and Korupolu, Radha and Kim, Sam and O{\textquoteright}Malley, Marcia K and Fregni, Felipe and Francisco, Gerard E} } @article {1777, title = {Design and optimization of an EEG-based brain machine interface (BMI) to an upper-limb exoskeleton for stroke survivors}, journal = {Frontiers in Neuroscience}, volume = {10}, year = {2016}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/FINS2016.pdf}, author = {Bhagat, N.A. and Venkatakrishnan, A. and Abibullaev, B. and Artz, E.J. and Yozbatiran, N. and Blank, A.A. and French, J. and Karmonik, C. and Grossman, R.G. and O{\textquoteright}Malley, M.K. and Francisco, G. and Contreras-Vidal, J.L.} } @article {1787, title = {Transcranial direct current stimulation (tDCS) of the primary motor cortex and robot-assisted arm training in chronic incomplete cervical spinal cord injury: A proof of concept sham-randomized clinical study}, journal = {NeuroRehabilitation}, volume = {39}, year = {2016}, pages = {401{\textendash}411}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/TDCS_2016_Neurorehab.pdf}, author = {Nuray Yozbatirana and Zafer Keser and Matthew Davis and Argyrios Stampas and Marcia K. O{\textquoteright}Malley and Catherine Cooper-Hay and Joel Fronteraa and Felipe Fregni and Gerard E. Francisco} } @proceedings {1842, title = {Characterization of a hand-wrist exoskeleton, READAPT, via kinematic analysis of redundant pointing tasks}, year = {2015}, publisher = {IEEE}, address = {Singapore}, doi = { 10.1109/ICORR.2015.7281200}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/ICORR15_0190_MS_0.pdf}, author = {Rose, Chad G. and Sergi, Fabrizio and Yun, Youngmok and Madden, Kaci and Deshpande, Ashish D and O{\textquoteright}Malley, Marcia K} } @proceedings {1752, title = {Design of a parallel-group balanced controlled trial to test the effects of assist-as-needed robotic therapy}, year = {2015}, month = {08/2015}, address = {Singapore}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Sergi2015\%20-\%20Design\%20parallel\%20group\%20AAN\%20therapy.pdf}, author = {Sergi, F. and Pehlivan, A.U. and Fitle, K. and Nedley, K. and Yozbatiran, Nuray and Francisco,Gerard E. and O{\textquoteright}Malley, M.K.} } @article {1760, title = {An index finger exoskeleton with series elastic actuation for rehabilitation: Design, control and performance characterization}, journal = {International Journal of Robotics Research}, volume = {34}, number = {14}, year = {2015}, pages = {1747-1772}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Agarwal2015\%20-\%20Index\%20finger\%20exo.pdf}, author = {Priyanshu Agarwal and Jonas Fox and Youngmok Yun and O{\textquoteright}Malley, M.K. and Ashish D. Deshpande} } @article {ROB:9438993, title = {Design and validation of the RiceWrist-S exoskeleton for robotic rehabilitation after incomplete spinal cord injury}, journal = {Robotica}, volume = {32}, year = {2014}, month = {12}, pages = {1415{\textendash}1431}, issn = {1469-8668}, doi = {10.1017/S0263574714001490}, url = {http://journals.cambridge.org/article_S0263574714001490}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/rob1400149_Press.pdf}, author = {Pehlivan,Ali Utku and Sergi,Fabrizio and Erwin,Andrew and Yozbatiran,Nuray and Francisco,Gerard E. and O{\textquoteright}Malley,Marcia K.} } @proceedings {1882, title = {Detecting movement intent from scalp EEG in a novel upper limb robotic rehabilitation system for stroke}, year = {2014}, month = {08/2014}, keywords = {Accuracy, Adult, bioelectric potentials, brain-computer interfaces, closed loop systems, closed-loop brain-machine interfaces, Computer-Assisted, diseases, electroencephalography, Electromyography, Exoskeletons, hemiparesis, Humans, Male, medical robotics, medical signal detection, medical signal processing, Middle Aged, Movement, movement intent detection, neurophysiology, Paresis, Patient rehabilitation, Robotics, Robots, scalp electroencephalography, Signal Processing, stroke, stroke rehabilitation, Support Vector Machine, Support vector machines, training, Upper Extremity, upper extremity dysfunction, upper limb robotic rehabilitation system, Young Adult}, doi = {10.1109/EMBC.2014.6944532}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/bhagat2014ieee.pdf}, author = {N. A. Bhagat and J. French and A. Venkatakrishnan and N. Yozbatiran and G. E. Francisco and M. K. O{\textquoteright}Malley and J. L. Contreras-Vidal} } @article {1563, title = {The RiceWrist Grip: A Means to Measure Grip Strength of Patients Using the RiceWrist}, year = {2012}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/grip_sensor_poster_mission_connect_0.pdf}, author = {Ryan Quincy and Andrew Erwin and A.U. Pehlivan and Yozbatiran, Nuray and Gerard Francisco and Marcia K. O{\textquoteright}Malley} } @article {1468, title = {RiceWrist Robotic Device for Upper Limb Training: Feasibility Study and Case Report of Two Tetraplegic Persons with Spinal Cord Injury}, journal = {International Journal of Biological Engineering}, volume = {2}, number = {4}, year = {2012}, pages = {27-38}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/IntlJBiologicalEngineering_2012_Kadivar.pdf}, author = {Z. Kadivar and J.L. Sullivan and D.P. Eng and A.U. Pehlivan and O{\textquoteright}Malley, M.K. and N. Yozbatiran and G.E. Francisco} } @article {1698, title = {Robotic training and clinical assessment of upper extremity movements after spinal cord injury; a single case report}, journal = {Journal of Rehabilitation Medicine}, volume = {44}, year = {2012}, month = {01/2012}, pages = {186-188}, chapter = {186}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/J_Rehab_Medicine_2012_Final_press_version.pdf}, author = {Yozbatiran, Nuray and Berliner, J. and O{\textquoteright}Malley, M.K. and Pehlivan, A.U. and Z. Kadivar and Boake, Corwin and Gerard E. Francisco} } @proceedings {1880, title = {Robotic training and clinical assessment of forearm and wrist movements after incomplete spinal cord injury: A case study}, year = {2011}, month = {June}, pages = {619-622}, abstract = {

The effectiveness of a robotic training device was evaluated in a 24-year-old male, cervical level four, ASIA Impairment Scale D injury. Robotic training of both upper extremities was provided for three hr/day for ten consecutive sessions using the RiceWrist, an electrically-actuated forearm and wrist haptic exoskeleton device that has been designed for rehabilitation applications. Training involved wrist flexion/extension, radial/ulnar deviation and forearm supination/pronation. Therapy sessions were tailored, based on the patient{\textquoteright}s movement capabilities for the wrist and forearm, progressed gradually by increasing number of repetitions and resistance. Outcome measures included the ASIA upper-extremity motor score, grip and pinch strength, the Jebsen-Taylor Hand Function test and the Functional Independence Measure. After the training, improvements were observed in pinch strength, and functional tasks. The data from one subject provides valuable information on the feasibility and effectiveness of robotic-assisted training of forearm and hand functions after incomplete spinal cord injury.

}, keywords = {age 24 yr, arm motor function recovery, ASIA upper-extremity motor score, biomechanics, clinical assessment, electrically-actuated forearm, Forearm, forearm movement, forearm pronation, forearm supination, functional independence measure, functional tasks, grip, Haptic interfaces, Humans, injuries, Jebsen-Taylor hand function test, Joints, Male, medical robotics, Medical treatment, Muscles, neurophysiology, patient movement capabilities, Patient rehabilitation, Patient treatment, pinch strength, radial-ulnar deviation, rehabilitation applications, robotic training, Robots, Spinal Cord Injuries, spinal cord injury, training, Wrist, wrist extension, wrist flexion, wrist haptic exoskeleton device, wrist movement, Young Adult}, doi = {10.1109/ICORR.2011.5975425}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/yozbatiran2011ieee.pdf}, author = {N. Yozbatiran and J. Berliner and C. Boake and M. K. O{\textquoteright}Malley and Z. Kadivar and G. E. Francisco} } @proceedings {1293, title = {Robotic Training and Kinematic Analysis of Arm and Hand after Incomplete Spinal Cord Injury: A Case Study.}, year = {2011}, month = {06/2011}, address = {Zurich Switzerland}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/1293-PID1757607\%5B1\%5D.pdf}, author = {Z. Kadivar and J.L. Sullivan and D.P. Eng and A.U. Pehlivan and M.K. O{\textquoteright}Malley and N. Yozbatiran and G.E.Francisco} } @article {911, title = {Normalized movement quality measures for therapeutic robots strongly correlate with clinical motor impairment measures}, journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering}, volume = {18}, number = {4}, year = {2010}, pages = {433-444}, abstract = {In this paper, we analyze the correlations between four clinical measures (Fugl{\textendash}Meyer upper extremity scale, Motor Activity Log, Action Research Arm Test, and Jebsen-Taylor Hand Function Test) and four robotic measures (smoothness of movement, trajectory error, average number of target hits per minute, and mean tangential speed), used to assess motor recovery. Data were gathered as part of a hybrid robotic and traditional upper extremity rehabilitation program for nine stroke patients. Smoothness of movement and trajectory error, temporally and spatially normalized measures of movement quality defined for point-to-point movements, were found to have significant moderate to strong correlations with all four of the clinical measures. The strong correlations suggest that smoothness of movement and trajectory error may be used to compare outcomes of different rehabilitation protocols and devices effectively, provide improved resolution for tracking patient progress compared to only pre- and post-treatment measurements, enable accurate adaptation of therapy based on patient progress, and deliver immediate and useful feedback to the patient and therapist.}, url = {http://dx.doi.org/10.1109/TNSRE.2010.2047600}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/911-Celik2010TNSRE.pdf}, author = {Ozkan Celik and O{\textquoteright}Malley, M.K. and Boake, Corwin and H.S. Levin and Yozbatiran, Nuray and Reistetter, Timothy} }